Probabilistic Graphical Models refers to i.) concise representations of probability distributions using graphs ii.) efficient algorithms for sampling distributions represented in such form iii.) learning these representations from data.
This course is intended to familiarize the students with the types of mathematical reasoning found in theoretical research on computing and communications. The course contains a broad set of intermediate and advanced level topics in Algebra, Combinatorics, Probability and Graph Theory.
Surveying Deep learning methods used in Reinforcement Learning